The invention relates to a method and a device for the acquisition of a range image. In contrast to conventional images which code gray scales or colors, range images code the distance of object points from the sensor (usually a camera) or the height of the object points relative to a plane. The pixels of a range image thus comprise range information (e.g. distance or height) of each corresponding imaged object point. Technical applications are found, inter alia, in assembly control, in robotics, metrology, archeology, in the textile industry, in biometrics, medicine and reverse engineering.
An overview of the methods used as well as a table of commercially available systems are found in the literature reference “Review of 20 years of range sensor development”, Journal of Electronic Imaging, 13 (1): 231-240, January 2004, National Research Council Canada. For more information about the methods, see also Paul J. Besl, “Active Optical Range Imaging sensors, Machine Vision and Applications” (1988) 1:127-152.
The method described in this application relates to the triangulation with stereo cameras for the contact-free acquisition of a range image. Conventional stereo systems use two or more video cameras which are rigidly connected with each other and observe the same scene. With stereo methods, the most difficult problem is to establish the correspondence between the pixels, i.e. to allocate the pixels of the one camera to the pixels of the other camera. When the correspondence is known, a corresponding range image can be calculated according to known mathematical methods (see e.g. Yi Ma, Stefano Soatto, Jana Kosecka, S. Shankar Sastry: “An Invitation to 3D”, Springer Verlag 2004).
To establish correspondence, classic image analysis methods are used on the basis of the extraction of contour-like or blob-like features; however, due to possible problems in the extraction of features, an allocation found is not really certain; in addition, it must be estimated or interpolated between the features. To circumvent these problems, structured light is additionally used.
With regularly repeating light structures, such as the widespread strip patterns, ambiguities will occur which can be eliminated by the coded light approach. Usually, a single camera is used here, with the geometry of the light source itself used for the triangulation. An overview of known techniques is provided by the literature reference J. Battle, E. Mouaddib, J. Salvi: “Recent Progress in Coded Structured Light as a Technique to Solve the Correspondence Problem—A Survey”. Pattern Recognition, Vol. 31, No. 7, p. 963-982, 1998.
The publication WO 2005/010825 A2 discloses a method for the acquisition of a range image in which a first illumination of the scene (object) is performed with a random pattern (random grid) and a second illumination with a so-called “striped grid”. A first and a second image is taken by two cameras each. In a first step after taking the first images with both cameras, the correspondence between the coordinates of the two first images is determined. After the second images are taken, the correspondence established in the first step is used to identify pattern strips between the two second images of the scene. Finally, the scene's 3D coordinates are determined for example by means of triangulation. Brightness ratios from the first and the second image are not calculated for both cameras, and no correspondence of pixels will be performed on the basis of a comparison of the brightness ratios.
In J. Salvi, J. Pagès, J. Battle, “Pattern codification strategies in structured light system”, Pattern Recognition 37, 2004, pages 827-849, it was proposed to use one camera to take a plurality of images of one scene with different illumination patterns and to subsequently calculate for each image the brightness ratio (intensity ratio) relative to constant illumination. However, no random or pseudo random patterns are used, and there is also no indication for the comparison of brightness ratios of the images taken by two cameras.
According to U.S. Pat. No. 6,542,250 B1, at least two patterns are used which can be random patterns. On the basis of an initial estimation, an iterative process realizes, point by point, a forward calculation of spatial coordinates to image coordinates of two cameras, with a refinement in every iterative step.
It is also known to work with individual textured illumination patterns and textured element-wise correspondence determination, e.g. with the systems of companies 3Q/3DMD (see http://www.3dmd.com/AboutUs/Technology.asp). This has the disadvantage that the textured elements can appear differently from different angles of view (sheen, shading, form). As such, they are difficult to analyze and thus may provide uncertain results. Consequently, these methods are only used on not excessively structured surfaces with a broad reflection club (mat surfaces). According to D. Viejo, J. M. Sa'z, M. A. Cazorla, F. Escolano: “Active Stereo Based Compact Mapping. Proc. of the IEEE/RSJ Intern. Conf. on Intell. Robots and Systems”, Canada, August 2005, the problem is eased by a specifically selected form of the features, namely by line elements of randomly changing brightness and orientation; only elements of matching orientation and brightness may be paired with each other. It is disadvantageous in this respect that a) the brightness differs viewed from different directions and that b) these zo elements must have a certain expansion for a reliable analysis, which is why the acquisition of a pixel-wise correspondence again requires interpolation between the features.
According to J. Battle, E. Mouaddib, J. Salvi: “Recent Progress in Coded Structured Light as a Technique to Solve the Correspondence Problem. A Survey”. Pattern Recognition, Vol. 31, No. 7, p. 963-982, 1998, p. 841-842, paragraph 5.1, one camera is used to take a plurality of images of one scene with different illumination patterns in each case. Subsequently, the corresponding brightness ratio (intensity ratio) is calculated for each image in relation to a constant illumination (codification based on grey levels).
A special form of coded light is the coding by means of a color pattern continuously running over the field of vision (“rainbow”), with an individual camera, according to JP 61075210 or U.S. Pat. No. 5,675,407. One problem here is the high price for the projector which is realized e.g. by means of a linear variable wavelength filter.
According to U.S. Pat. No. 6,028,672, with continuously running color patterns, the triangulation does not take place between camera and projector, but between two cameras, with a color comparison on epipolar lines of the two cameras. It actually eases the requirement of a geometrically precise color projection, because random color patterns can thus be used; however, basic problems will remain with the color analysis.
According to U.S. Pat. No. 6,556,706, these problems are to be reduced by means of various measures, among others by means of a light projection containing, sheet wise, only the light of one wavelength (see e.g. column 5, line 35 “ . . . impose a single spectral light condition to the projector”).
The same applicant also proposed arrangements with a rotating laser light slot (see U.S. Pat. No. 6,600,168), with one camera, with the light brightness changing depending on the angle, increasing for one image capture and decreasing for another image capture (hereinafter called “countercurrent”). Via the brightness ratio of a pixel from the images, an unambiguous allocation to the corresponding angle of projection can be obtained. Disadvantageous are the mechanical movement and the required precision in the projection.
A static arrangement for creating countercurrent illumination patterns over the field of vision, with one camera, is described in U.S. Pat. No. 6,897,946, generated by two closely neighboring lamps slightly turned away from each other, with reflectors.
Another device for the creation of countercurrent illumination patterns over the field of vision is described in U.S. Pat. No. 6,618,123, with a field of LEDs which are controlled such that countercurrent illumination patterns develop over the field of vision. The device operates with a single camera and requires homogeneous light beams and an elaborate calibration with a planar plate.
A general disadvantage of methods with continuous, countercurrent illumination patterns over the field of vision is the fact that—with a planar base—the brightness values of neighboring pixels differ only slightly and a precise local allocation is therefore difficult.
To achieve, nonetheless, good allocation (and thus a good range measurement), high-resolution precision transducers must be used. In order to utilize well the illumination dynamics with low brightness values and to be able to analyze well even dark surface sections, the ratio has to be calculated by means of a division by small numbers; accordingly, even with small numbers, adequately significant bits must be available. When two cameras are used, they must be precisely matched with each other.
Taking this state of the art into account, it is an object of the invention to provide a method and a device which avoid the above-mentioned disadvantages.